CTI 2: Does culture play a role?

Author: Ching Hu 

Culture, remarked the critic and novelist Raymond Williams, is one of the most complicated words in the English language. Yet world traveller, linguist, and consultant Richard Lewis, who speaks 10 languages and was once tutor to Empress Michiko of Japan, thinks that all of the world’s different cultures can be plotted on a single chart. In his “authoritative” (the Wall Street Journal) book “When Cultures Collide” (first published 1996), Lewis attempts to explain the behaviour of countries by grouping them into three main “cultural types

Linear-Active cultures are those which contain “cool, factual and decisive planners”, and include Germany, Switzerland and Luxembourg, amongst others. Multi-Active people are typically “warm, emotional, loquacious and impulsive”, as exemplified by the Argentineans, Mexicans, Brazilians and Chileans. On the other hand, those who are courteous, amiable, accommodating, listen well and are able to compromise are termed Re-Actives. Examples include the people of Vietnam, China and Japan.

Yet just how important is the role of culture in explaining national differences in carbon emissions? To find out, I borrowed Lewis’ Model as a framework and used data from the World Bank. First, I worked with Gross Domestic Product (GDP, measured in terms of current US dollars) per capita and carbon emission (measured in terms of metric tons) per capita figures. For each “cultural type”, I worked out the average carbon emission/US$1 GDP per capita, after eliminating outliers* within each “cultural type”.

               It turns out that the calculated figures for Multi-Active (0.33) and Linear-Active (0.20) “cultural types” were quite small. Interestingly, the calculated figure for the Re-Active group (0.82) is much higher than the other two groups, indicating that Re-Actives emit more carbon for every US$1 of GDP.

               Turning our attention to the Gross National Income based on Purchasing Power Parity (PPP GNI, measured in terms of current international dollars), a similar conclusion can be reached. The corresponding carbon emission/PPP GNI average for the Re-Actives (0.44) is about double that of the Multi-actives’ (0.24) and the Linear-Actives’ (0.22).

               One might attribute the relatively high carbon emission/PPP GNI average for the Re-Actives to the performances of Thailand and Vietnam – countries with a low PPP GNI figure of less than 8,000 current international dollars. However, it would not be entirely right to do so. Other countries with low PPP GNI figures, such as the Sub-Saharan African countries listed in this study, do not always emit more carbon than PPP GNI per capita. On the other end of the PPP GNI spectrum, wealthy countries such as the United States and Luxembourg emit more carbon per PPP GNI dollar compared less wealthy countries such as Slovenia and Latvia.

               The results of this simple investigation may not be conclusive, due to the small sample size of countries, as well as the accuracy of Lewis’ framework of “cultural types”. Nevertheless, there is plenty of room and potential for further research on this inquiry. Could cultural traits such as the emphasis on face-to-face contact or the adoption of a non-confrontational approach hamper the progress of the Re-Actives during climate conferences? Or could it be that talking more for the Multi-Actives and Linear-Actives enable politicians from those countries to push for more climate-friendly national policies? If so, then psychologists, linguists and cultural experts may have a more important role than previously thought in steering the world towards a sustainable future.

by Ching Hu

*For each “cultural type”, I first worked out the raw average carbon emission/US$1 GDP per capita and the standard deviation. Following which, I removed outliers which had a figure beyond +1/-1 standard deviation. Only remaining data was used to calculate the treated average.

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